Much research has recently centered on converging disparate wireless networks. One such convergence relative to the examples herein is that of wireless sensor networks with a cellular wireless telecommunication network. Such a convergence can potentially extend the services that each network might provide; the cellular network can manage/control devices of the sensor network for monitoring and data collection while the wireless sensor network can utilize the telecommunication network to share its information with other networks. For example, some network-operator members of the Third Generation Partnership Project (3GPP) have expressed interest in utilizing cellular user equipments (UEs) as gateways/data collection sinks for what 3GPP terms capillary networks which can be wireless sensor networks.
Traditional wireless sensor networks relied upon a single data sink to collect the data from all the other sensors via multi-hop transmissions through the network. Of course those devices within one hop of the sink tend to become data bottlenecks, which increases their energy consumption. To the extent these devices rely on a battery/galvanic or other finite power source they would go offline once their energy source was depleted, resulting in partition of the network topology. Mobile data sinks have been proposed as a solution so as to geographically balance the energy consumption among the sensor nodes throughout the sensor network. This also distributes the responsibility of relaying data to the sink among many nodes in the sensor network. As mentioned above, one option to converge the telecommunication and wireless sensor networks is to utilize devices with cellular interfaces as the mobile sinks.
Converging these types of networks using a mobile UE brings efficiency challenges. Without mobile data sinks the conventional static sensor networks employed a static and fixed data collection topology to collect the network-wide data. Using a mobile data sink the data collection topology at one time is not sufficient at another time due to the data sink's mobility, and so the data collection topology needs to be constructed or updated from time to time according to the mobile UE's movement. But to directly adopt the traditional data collection paradigm would result in building a series of independent data collection topologies when the mobile user at different positions. This introduces a large volume of communication control overhead, and these topology transitions are seen to result in some time delay that may lead to discontinuity or even loss of the data delivered to the mobile user, thus reducing the quality of service (QoS) of the data collection.
Relevant background teachings may be seen in a paper by Shuai Gao, Hongke Zhang, and Sajal K. Das entitled EFFICIENT DATA COLLECTION IN WIRELESS SENSOR NETWORKS WITH PATH-CONSTRAINED MOBILE SINKS (IEEE Transactions on Mobile Computing, vol. 10, no. 5; pages 592-608; 2011). One limitation there is that it assumes the mobile sink moves along a constrained path (termed a Maximum Amount Shortest Path or MASP). Sensors out of the range of the sink are assigned to corresponding subsinks within the range of the sink according to the length of the communication time between the mobile sink and the subsinks to improve network throughput. But in many deployments the planned or accurately predicted mobility path for a mobile sink is not a valid assumption.
Further background is detailed in a paper by Xinxin Liu, Han Zhao, Xin Yang and Xiaolin Li entitled TRAILING MOBILE SINKS: A PROACTIVE DATA REPORTING PROTOCOL FOR WIRELESS SENSOR NETWORKS (IEEE Transactions on Computers; pages 214-223; 2011). This paper describes a proactive data reporting protocol termed SinkTrail in which each sensor node keeps its logical distance to the mobile sink and when it wants to route data to the mobile sink the sensor selects the next hop with the shortest logical distance to the mobile sink. But increasing the scale of a SinkTrail type of network is seen to result in frequent message flooding, which will cause congestion and impair the network's lifetime.